English Teacher's Modeling and Deep Learning in Overcoming Students' Vocabulary and Speaking Confidence Issues

Abstract

This study looks at how modeling and deep learning methods are used in teaching English and how they affect vocabulary knowledge and speaking confidence among fifth graders at Tandrawana Public Elementary School 074039. The research used a qualitative approach, involving one English teacher and 20 students. Data were collected through classroom observations, semi-structured interviews with the teacher, and document analysis of the ATP (Flow of Learning Objectives) and observation sheets. The data were analyzed using an interactive model consisting of data reduction, data display, and conclusion drawing. To ensure credibility and trustworthiness, triangulation was applied by cross-checking findings from observations, interviews, and documents. This study contributes to existing literature by integrating modeling and deep learning in a real elementary EFL classroom and demonstrating that deep learning activities need to be pedagogically adapted to match primary students’ cognitive and linguistic development. The results showed that the teacher often used modeling by practicing pronunciation, using simple sentences, and having students repeat dialogues. Deep learning was used through visual aids, group work, and exercises that helped students understand and think about vocabulary more deeply. The study found that these methods helped improve students' vocabulary and speaking confidence. However, some activities, like role-playing, were not used as effectively because the students had limited analytical abilities. Overall, using both modeling and deep learning helps students develop their vocabulary and speaking skills, but the way these methods are applied should match the thinking level of elementary school students.